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Oscar Martínez-Alvarado, Suzanne L. Gray, and John Methven

beginning of the study period. In spite of this, the simulations can be considered a realistic representation of the development of both cyclones. Several quantities derived from the dropsonde observations during the first IOP13 leg are shown in a vertical cross section in Figs. 2a and 2c . Figure 2a shows zonal velocity u , θ , and relative humidity with respect to ice ; Fig. 2c shows and water vapor flux defined as , where q is specific humidity and is the horizontal wind component

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Jeffrey M. Chagnon and Suzanne L. Gray

represent subgridscale processes. The model uses an Arakawa C grid in the horizontal with Charney–Phillips staggering in the vertical. The MetUM utilizes a height-based terrain-following vertical coordinate. Davies et al. (2005) provide a comprehensive summary of the model’s design. The parameterization schemes include the mass-flux convection scheme of Gregory and Rowntree (1990) , the MOSES-II boundary layer scheme ( Lock et al. 2000 ), the Edwards and Slingo (1996) radiation scheme, and the

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David M. Schultz and Joseph M. Sienkiewicz

Fritsch 1990 , 1993 ; Kain 2004 ), the Noah land surface model ( Chen and Dudhia 2001 ), the Rapid Radiative Transfer Model for short- and longwave radiation ( Mlawer et al. 1997 ), and Lin et al.'s microphysics ( Lin et al. 1983 ; Rutledge and Hobbs 1984 ; Tao et al. 1989 ; Chen and Sun 2002 ). No data assimilation or nudging was used. Although the winds associated with the sting jet occur specifically at the surface, wind speeds in this article are plotted at 925 hPa because frontal structures

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G. Vaughan, J. Methven, D. Anderson, B. Antonescu, L. Baker, T. P. Baker, S. P. Ballard, K. N. Bower, P. R. A. Brown, J. Chagnon, T. W. Choularton, J. Chylik, P. J. Connolly, P. A. Cook, R. J. Cotton, J. Crosier, C. Dearden, J. R. Dorsey, T. H. A. Frame, M. W. Gallagher, M. Goodliff, S. L. Gray, B. J. Harvey, P. Knippertz, H. W. Lean, D. Li, G. Lloyd, O. Martínez–Alvarado, J. Nicol, J. Norris, E. Öström, J. Owen, D. J. Parker, R. S. Plant, I. A. Renfrew, N. M. Roberts, P. Rosenberg, A. C. Rudd, D. M. Schultz, J. P. Taylor, T. Trzeciak, R. Tubbs, A. K. Vance, P. J. van Leeuwen, A. Wellpott, and A. Woolley

by diabatic processes (those that add or remove heat from the air) such as latent heating and cooling associated with phase changes of water, fluxes of heat and moisture from the Earth’s surface, and radiative flux convergence. Key elements in diabatic processes are turbulence, convection, and cloud physics—small-scale phenomena that cannot be represented explicitly in numerical weather prediction models. They must therefore be parameterized, introducing a source of systematic uncertainty in the

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Oscar Martínez-Alvarado, Laura H. Baker, Suzanne L. Gray, John Methven, and Robert S. Plant

developed to study the creation and destruction of potential vorticity ( Stoelinga 1996 ; Gray 2006 ). Potential temperature is decomposed in a series of tracers so that . Each tracer Δ θ P accumulates the changes in θ that can be attributed to the parameterized process P . The parameterized processes considered in this work are (i) surface fluxes and turbulent mixing in the boundary layer, (ii) convection, (iii) radiation, and (iv) large-scale cloud and precipitation. The tracer θ 0 matches θ

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Sam Hardy, David M. Schultz, and Geraint Vaughan

University planetary boundary layer scheme ( Hong et al. 2006 ), Noah land surface model, and the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) similarity surface-layer scheme, based on Monin–Obukhov theory ( Monin and Obukhov 1954 ). Longwave and shortwave radiation were parameterized using the Rapid Radiative Transfer Model for general circulation models (RRTMG) scheme ( Iacono et al. 2008 ), and the Kain–Fritsch scheme ( Kain and Fritsch

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